About this dataset

Context

The dataset tabulates the Illinois population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Illinois across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2024, the population of Illinois was 12.71 million, a 0.54% increase year-by-year from 2023. Previously, in 2023, Illinois population was 12.64 million, an increase of 0.16% compared to a population of 12.62 million in 2022. Over the last 20 plus years, between 2000 and 2024, population of Illinois increased by 272,590. In this period, the peak population was 12.9 million in the year 2009. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2024

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2024)
• Population: The population for the specific year for the Illinois is shown in this column.
• Year on Year Change: This column displays the change in Illinois population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Illinois Population by Year. You can refer the same here

About this dataset

Context

The dataset tabulates the Illinois population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Illinois across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2022, the population of Illinois was 12,582,032, a 0.82% decrease year-by-year from 2021. Previously, in 2021, Illinois population was 12,686,469, a decline of 0.78% compared to a population of 12,786,580 in 2020. Over the last 20 plus years, between 2000 and 2022, population of Illinois increased by 144,464. In this period, the peak population was 12,897,476 in the year 2009. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2022

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2022)
• Population: The population for the specific year for the Illinois is shown in this column.
• Year on Year Change: This column displays the change in Illinois population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Illinois Population by Year. You can refer the same here

Introduction This report presents projections of population from 2015 to 2025 by age and sex for Illinois, Chicago and Illinois counties produced for the Certificate of Need (CON) Program. As actual future population trends are unknown, the projected numbers should not be considered a precise prediction of the future population; rather, these projections, calculated under a specific set of assumptions, indicate the levels of population that would result if our assumptions about each population component (births, deaths and net migration) hold true. The assumptions used in this report, and the details presented below, generally assume a continuation of current trends. Methodology These projections were produced using a demographic cohort-component projection model. In this model, each component of population change – birth, death and net migration – is projected separately for each five-year birth cohort and sex. The cohort – component method employs the following basic demographic balancing equation: P1 = P0 + B – D + NM Where: P1 = Population at the end of the period; P0 = Population at the beginning of the period; B = Resident births during the period; D = Resident deaths during the period; and NM = Net migration (Inmigration – Outmigration) during the period. The model roughly works as follows: for every five-year projection period, the base population, disaggregated by five-year age groups and sex, is “survived” to the next five-year period by applying the appropriate survival rates for each age and sex group; next, net migrants by age and sex are added to the survived population. The population under 5 years of age is generated by applying age specific birth rates to the survived females in childbearing age (15 to 49 years). Base Population These projections began with the July 1, 2010 population estimates by age and sex produced by the U.S. Census Bureau. The most recent census population of April 1, 2010 was the base for July 1, 2010 population estimates. Special Populations In 19 counties, the college dormitory population or adult inmates in correctional facilities accounted for 5 percent or more of the total population of the county; these counties were considered as special counties. There were six college dorm counties (Champaign, Coles, DeKalb, Jackson, McDonough and McLean) and 13 correctional facilities counties (Bond, Brown, Crawford, Fayette, Fulton, Jefferson, Johnson, Lawrence, Lee, Logan, Montgomery, Perry and Randolph) that qualified as special counties. When projecting the population, these special populations were first subtracted from the base populations for each special county; then they were added back to the projected population to produce the total population projections by age and sex. The base special population by age and sex from the 2010 population census was used for this purpose with the assumption that this population will remain the same throughout each projection period. Mortality Future deaths were projected by applying age and sex specific survival rates to each age and sex specific base population. The assumptions on survival rates were developed on the basis of trends of mortality rates in the individual life tables constructed for each level of geography for 1989-1991, 1999-2001 and 2009-2011. The application of five-year survival rates provides a projection of the number of persons from the initial population expected to be alive in five years. Resident deaths data by age and sex from 1989 to 2011 were provided by the Illinois Center for Health Statistics (ICHS), Illinois Department of Public Health. Fertility Total fertility rates (TFRs) were first computed for each county. For most counties, the projected 2015 TFRs were computed as the average of the 2000 and 2010 TFRs. 2010 or 2015 rates were retained for 2020 projections, depending on the birth trend of each county. The age-specific birth rates (ASBR) were next computed for each county by multiplying the 2010 ASBR by each projected TFR. Total births were then projected for each county by applying age-specific birth rates to the projected female population of reproductive ages (15 to 49 years). The total births were broken down by sex, using an assumed sex-ratio at birth. These births were survived five years applying assumed survival ratios to get the projected population for the age group 0-4. For the special counties, special populations by age and sex were taken out before computing age-specific birth rates. The resident birth data used to compute age-specific birth rates for 1989-1991, 1999-2001 and 2009-2011 came from ICHS. Births to females younger than 15 years of age were added to those of the 15-19 age group and births to women older than 49 years of age were added to the 45-49 age group. Net Migration Migration is the major component of population change in Illinois, Chicago and Illinois counties. The state is experiencing a significant loss of population through internal (domestic migration within the U.S.) net migration. Unlike data on births and deaths, migration data based on administrative records are not available on a regular basis. Most data on migration are collected through surveys or indirectly from administrative records (IRS individual tax returns). For this report, net migration trends have been reviewed using data from different sources and methods (such as residual method) from the University of Wisconsin, Madison, Illinois Department of Public Health, individual exemptions data from the Internal Revenue Service, and survey data from the U.S. Census Bureau. On the basis of knowledge gained through this review and of levels of net migration from different sources, assumptions have been made that Illinois will have annual net migrants of -40, 000, -35,000 and -30,000 during 2010-2015, 2015-2020 and 2020-2025, respectively. These figures have been distributed among the counties, using age and sex distribution of net migrants during 1995-2000. The 2000 population census was the last decennial census, which included the question “Where did you live five years ago?” The age and sex distribution of the net migrants was derived, using answers to this question. The net migration for Chicago has been derived independently, using census survival method for 1990-2000 and 2000-2010 under the assumption that the annual net migration for Chicago will be -40,000, -30,000 and -25,000 for 2010-2015, 2015-2020 and 2020-2025, respectively. The age and sex distribution from the 2000-2010 net migration was used to distribute the net migrants for the projection periods. Conclusion These projections were prepared for use by the Certificate of Need (CON) Program; they are produced using evidence-based techniques, reasonable assumptions and the best available input data. However, as assumptions of future demographic trends may contain errors, the resulting projections are unlikely to be free of errors. In general, projections of small areas are less reliable than those for larger areas, and the farther in the future projections are made, the less reliable they may become. When possible, these projections should be regularly reviewed and updated, using more recent birth, death and migration data.

About this dataset

Context

The dataset tabulates the data for the Illinois population pyramid, which represents the Illinois population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey 5-Year estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Illinois, is 28.1.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Illinois, is 23.9.
• Total dependency ratio for Illinois is 52.0.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Illinois is 4.2.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group for the Illinois population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Illinois for the selected age group is shown in the following column.
• Population (Female): The female population in the Illinois for the selected age group is shown in the following column.
• Total Population: The total population of the Illinois for the selected age group is shown in the following column.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Illinois Population by Age. You can refer the same here

DEC. 22, 2022 – After a historically low rate of change between 2020 and 2021, the U.S. resident population increased by 0.4%, or 1,256,003, to 333,287,557 in 2022, according to the U.S. Census Bureau’s Vintage 2022 national and state population estimates and components of change released today.

Net international migration — the number of people moving in and out of the country — added 1,010,923 people between 2021 and 2022 and was the primary driver of growth. This represents 168.8% growth over 2021 totals of 376,029 – an indication that migration patterns are returning to pre-pandemic levels. Positive natural change (births minus deaths) increased the population by 245,080.

“There was a sizeable uptick in population growth last year compared to the prior year’s historically low increase,” said Kristie Wilder, a demographer in the Population Division at the Census Bureau. “A rebound in net international migration, coupled with the largest year-over-year increase in total births since 2007, is behind this increase.”

Regional Patterns The South, the most populous region with a resident population of 128,716,192, was the fastest-growing and the largest-gaining region last year, increasing by 1.1%, or 1,370,163. Positive net domestic migration (867,935) and net international migration (414,740) were the components with the largest contributions to this growth, adding a combined 1,282,675 residents.

The West was the only other region to experience growth in 2022, having gained 153,601 residents — an annual increase of 0.2% for a total resident population of 78,743,364 — despite losing 233,150 residents via net domestic migration (the difference between residents moving in and out of an area). Natural increase (154,405) largely accounted for the growth in the West.

The Northeast, with a population of 57,040,406, and the Midwest, with a population of 68,787,595, lost 218,851 (-0.4%) and 48,910 (-0.1%) residents, respectively. The declines in these regions were due to negative net domestic migration.

Changes in State Population Increasing by 470,708 people since July 2021, Texas was the largest-gaining state in the nation, reaching a total population of 30,029,572. By crossing the 30-million-population threshold this past year, Texas joins California as the only states with a resident population above 30 million. Growth in Texas last year was fueled by gains from all three components: net domestic migration (230,961), net international migration (118,614), and natural increase (118,159).

Florida was the fastest-growing state in 2022, with an annual population increase of 1.9%, resulting in a total resident population of 22,244,823.

“While Florida has often been among the largest-gaining states,” Wilder noted, “this was the first time since 1957 that Florida has been the state with the largest percent increase in population.”

It was also the second largest-gaining state behind Texas, with an increase of 416,754 residents. Net migration was the largest contributing component of change to Florida’s growth, adding 444,484 residents. New York had the largest annual numeric and percent population decline, decreasing by 180,341 (-0.9%). Net domestic migration (-299,557) was the largest contributing component to the state’s population decline.

Eighteen states experienced a population decline in 2022, compared to 15 and DC the prior year. California, with a population of 39,029,342, and Illinois, with a population of 12,582,032, also had six-figure decreases in resident population. Both states’ declining populations were largely due to net domestic outmigration, totaling 343,230 and 141,656, respectively.

Puerto Rico Population Changes In 2022, Puerto Rico’s population was 3,221,789. This reflects a decrease of 1.3%, or 40,904 people, between 2021 and 2022.

Puerto Rico’s population decline resulted from negative net international migration (-26,447) and negative natural change (-14,457), where deaths outnumber births.

                            **###Components of Change for States**

In 2022, 24 states experienced negative natural change, or natural decrease. Florida had the highest natural decrease at -40,216, followed by Pennsylvania (-23,021) and Ohio (-19,543). In 2021, 25 states had natural decrease.

Of the 26 states and the District of Columbia where births outnumbered deaths, Texas (118,159), California (106,155) and New York (35,611) had the highest natural increase.

All 50 states and the District of Columbia saw positive net international migration with California (125,715), Florida (125,629) and Texas (118,614) having the largest gains.

The biggest gains from net domestic migration last year were in Florida (318,855), Texas (230,961) and North Carolina (99,796), while the biggest losses were in California (-343,230), New York (-299,557) and Illinois...

There are three components of change: births, deaths, and migration. The change in the population from births and deaths is often combined and referred to as natural increase or natural change. Populations grow or shrink depending on if they gain people faster than they lose them. Looking at an area’s unique combination of natural change and migration helps us understand why its population is changing, and how quickly the change is occurring.Natural IncreaseNatural change is the difference between births and deaths in a population. Often times, natural change is positive, which means that more babies are being born than people are dying. This positive natural change is referred to as natural increase. Examples of natural increase exist across the United States, one being the Salt Lake City metro area in Utah. Between 2014 and 2015, Salt Lake City had around 19,100 births and 6,400 deaths. Since there were about 12,700 more births than deaths, Salt Lake City had a natural increase of about 12,700 people, making natural increase a key reason why its population grew over the year.The opposite of natural increase is called natural decrease, where more people are dying than babies being born, which can cause a population to shrink. Areas with aging populations often have natural decrease. Two states had natural decrease between 2014 and 2015, Maine and West Virginia. Between 2014 and 2015, Maine had 450 more deaths than births and West Virginia had 940 more deaths than births. In both cases, natural decrease was one of the reasons why their populations shrank between 2014 and 2015 in our latest estimates.MigrationMigration is the movement of people from one area to another. It is often expressed as net migration, which is the difference between how many people move into and out of an area. When net migration is positive, a population has more people moving in than out. We split migration into domestic migration and international migration.Domestic migration refers to people moving between areas within the United States, and is often one of the largest contributors to population change. Regionally, the South gains the most net domestic migrants, with roughly 440,000 more people moving into southern states than leaving them between 2014 and 2015. Sometimes net domestic migration is negative, in which case more people are moving away than are moving in. The Chicago metro area in Illinois, Indiana, and Wisconsin lost about 80,000 people through migration between 2014 and 2015, which is consistent with a long-standing pattern of negative net domestic migration for the metro area.International migration refers to people moving into and out of the United States, and consists of a diverse group of people such as foreign-born immigrants from many countries around the world, members of the U.S. Armed Forces, and U.S. citizens working abroad. Some areas, like the Miami metro area in Florida, grow (in part) due to net international migration. Miami gained about 70,000 net international migrants between 2014 and 2015, making net international migration a major factor in Miami’s population growth.

To advance ON TO 2050’s commitment to inclusive growth, CMAP has defined Economically Disconnected and Disinvested Areas within the region. Economically Disconnected Areas (EDAs) identify areas with concentrations of both low-income households and population of color or limited English proficiency population; approximately one-third of the region’s population lives in EDAs. Disinvested Areas (DAs) outline primarily nonresidential places with long-term declines in employment and other markers of commercial market weakness. Together, EDA and DA communities experience a persistent, long-term lack of market investment, leading to declining property values, taxes, employment, and, frequently, population. Disinvestment often constrains the ability of any individual community to respond effectively to these losses, and high tax rates and low market potential limit private investment. For these reasons, these geographies should be examined both separately and together. While some policy solutions will be common to both geographies, other solutions may be unique to each geography.More information can be found on CMAP's Economically Disconnected and Disinvested Areas webpage.Data sources are detailed in the methodology documents linked below:EDA MethodologyDisinvested Areas MethodologyInclusive Growth Strategy PaperReinvestment and Infill Strategy Paper

Bumble bees (Bombus) are vitally important pollinators of wild plants and agricultural crops worldwide. Fragmentary observations, however, have suggested population declines in several North American species. Despite rising concern over these observations in the United States, highlighted in a recent National Academy of Sciences report, a national assessment of the geographic scope and possible causal factors of bumble bee decline is lacking. Here, we report results of a 3-y interdisciplinary study of changing distributions, population genetic structure, and levels of pathogen infection in bumble bee populations across the United States. We compare current and historical distributions of eight species, compiling a database of >73,000 museum records for comparison with data from intensive nationwide surveys of >16,000 specimens. We show that the relative abundances of four species have declined by up to 96% and that their surveyed geographic ranges have contracted by 23–87%, some within the last 20 y. We also show that declining populations have significantly higher infection levels of the microsporidian pathogen Nosema bombi and lower genetic diversity compared with co-occurring populations of the stable (nondeclining) species. Higher pathogen prevalence and reduced genetic diversity are, thus, realistic predictors of these alarming patterns of decline in North America, although cause and effect remain uncertain. Bumble bees (Bombus) are integral wild pollinators within native plant communities throughout temperate ecosystems, and recent domestication has boosted their economic importance in crop pollination to a level surpassed only by the honey bee. Their robust size, long tongues, and buzz-pollination behavior (high-frequency buzzing to release pollen from flowers) significantly increase the efficiency of pollen transfer in multibillion dollar crops such as tomatoes and berries. Disturbing reports of bumble bee population declines in Europe have recently spilled over into North America, fueling environmental and economic concerns of global decline. However, the evidence for large-scale range reductions across North America is lacking. Many reports of decline are unpublished, and the few published studies are limited to independent local surveys in northern California/southern Oregon, Ontario, Canada, and Illinois. Furthermore, causal factors leading to the alleged decline of bumble bee populations in North America remain speculative. One compelling but untested hypothesis for the cause of decline in the United States entails the spread of a putatively introduced pathogen, Nosema bombi, which is an obligate intracellular microsporidian parasite found commonly in bumble bees throughout Europe but largely unstudied in North America. Pathogenic effects of N. bombi may vary depending on the host species and reproductive caste and include reductions in colony growth and individual life span and fitness. Population genetic factors could also play a role in Bombus population decline. For instance, small effective population sizes and reduced gene flow among fragmented habitats can result in losses of genetic diversity with negative consequences, and the detrimental impacts of these genetic factors can be especially intensified in bees. Population genetic studies of Bombus are rare worldwide. A single study in the United States identified lower genetic diversity and elevated genetic differentiation (FST) among Illinois populations of the putatively declining B. pensylvanicus relative to those of a codistributed stable species. Similar patterns have been observed in comparative studies of some European species, but most investigations have been geographically restricted and based on limited sampling within and among populations. Although the investigations to date have provided important information on the increasing rarity of some bumble bee species in local populations, the different survey protocols and limited geographic scope of these studies cannot fully capture the general patterns necessary to evaluate the underlying processes or overall gravity of declines. Furthermore, valid tests of the N. bombi hypothesis and its risk to populations across North America call for data on its geographic distribution and infection prevalence among species. Likewise, testing the general importance of population genetic factors in bumble bee decline requires genetic comparisons derived from sampling of multiple stable and declining populations on a large geographic scale. From such range-wide comparisons, we provide incontrovertible evidence that multiple Bombus species have experienced sharp population declines at the national level. We also show that declining populations are associated with both high N. bombi infection levels and low genetic diversity. This data was used in the paper "Patterns of widespread decline in North American bumble bees" published in the Proceedings of the National Academy of United States of America. For more information about this dataset contact: Sydney A. Cameron: scameron@life.illinois.edu James Strange: James.Strange@ars.usda.gov Resources in this dataset:Resource Title: Data from: Patterns of Widespread Decline in North American Bumble Bees (Data Dictionary). File Name: meta.xmlResource Description: This is an XML data dictionary for Data from: Patterns of Widespread Decline in North American Bumble Bees.Resource Title: Patterns of Widespread Decline in North American Bumble Bees (DWC Archive). File Name: occurrence.csvResource Description: File modified to remove fields with no recorded values.Resource Title: Patterns of Widespread Decline in North American Bumble Bees (DWC Archive). File Name: dwca-usda-ars-patternsofwidespreaddecline-bumblebees-v1.1.zipResource Description: Data from: Patterns of Widespread Decline in North American Bumble Bees -- this is a Darwin Core Archive file. The Darwin Core Archive is a zip file that contains three documents. The occurrence data is stored in the occurrence.txt file. The metadata that describes the columns of this document is called meta.xml. This document is also the data dictionary for this dataset. The metadata that describes the dataset, including author and contact information for this dataset is called eml.xml. Find the data files at https://bison.usgs.gov/ipt/resource?r=usda-ars-patternsofwidespreaddecline-bumblebees

About this dataset

Context

The dataset tabulates the Freeport population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Freeport across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Freeport was 23,136, a 1.03% decrease year-by-year from 2022. Previously, in 2022, Freeport population was 23,376, a decline of 1.18% compared to a population of 23,655 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Freeport decreased by 3,196. In this period, the peak population was 26,332 in the year 2000. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Freeport is shown in this column.
• Year on Year Change: This column displays the change in Freeport population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Freeport Population by Year. You can refer the same here

Every 10 years, the number of seats a state has in the U.S. House of Representatives, and therefore the Electoral College, changes based on population. While many states experienced no change in representation due to the 2020 Census, a few states gained or lost seats. Texas notably gained *** seats due to an increase in population, while New York, Michigan, California, West Virginia, Pennsylvania, Ohio, and Illinois all lost *** seat.

This change will stay in place until 2030, when the next Census is conducted in the United States.

About this dataset

Context

The dataset tabulates the Cook County population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Cook County across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Cook County was 5.09 million, a 0.48% decrease year-by-year from 2022. Previously, in 2022, Cook County population was 5.11 million, a decline of 1.34% compared to a population of 5.18 million in 2021. Over the last 20 plus years, between 2000 and 2023, population of Cook County decreased by 289,679. In this period, the peak population was 5.38 million in the year 2000. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Cook County is shown in this column.
• Year on Year Change: This column displays the change in Cook County population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Cook County Population by Year. You can refer the same here

About this dataset

Context

The dataset tabulates the Decatur population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Decatur across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Decatur was 68,670, a 0.77% decrease year-by-year from 2022. Previously, in 2022, Decatur population was 69,201, a decline of 1.27% compared to a population of 70,088 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Decatur decreased by 13,169. In this period, the peak population was 81,839 in the year 2000. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Decatur is shown in this column.
• Year on Year Change: This column displays the change in Decatur population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Decatur Population by Year. You can refer the same here

About this dataset

Context

The dataset tabulates the Rockford population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Rockford across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Rockford was 146,120, a 0.36% decrease year-by-year from 2022. Previously, in 2022, Rockford population was 146,646, a decline of 0.74% compared to a population of 147,745 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Rockford decreased by 5,323. In this period, the peak population was 156,404 in the year 2008. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Rockford is shown in this column.
• Year on Year Change: This column displays the change in Rockford population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Rockford Population by Year. You can refer the same here

A central question in conservation is how best to manage biodiversity, despite human domination of global processes (= Anthropocene). Common responses (i.e. translocations, genetic rescue) forestall potential extirpations, yet have an uncertain duration. A textbook example is the greater prairie chicken (GRPC: Tympanuchus cupido pinnatus), where translocations (1992–1998) seemingly rescued genetically depauperate Illinois populations. We re-evaluated this situation after two decades by genotyping 21 microsatellite loci from 1831 shed feathers across six leks in two counties over 4 years (2010–2013). Low migration rates (less than 1%) established each county as demographically independent, but with declining-population estimates (4 year average N = 79). Leks were genetically similar and significantly bottlenecked, with low effective population sizes (average Ne = 13.1; 4 year Ne/N = 0.166). Genetic structure was defined by 12 significantly different family groups, with relatedness r = 0.31 > half-sib r = 0.25. Average heterozygosity, indicating short-term survival, did not differ among contemporary, pre- and post-translocated populations, whereas allelic diversity did. Our results, the natural history of GRPC (i.e. few leks, male dominance hierarchies) and its controlled immigration suggest demographic expansion rather than genetic rescue. Legal protection under the endangered species act (ESA) may enhance recovery, but could exacerbate political–economic concerns on how best to manage ‘conservation-reliant’ species, for which GRPC is now an exemplar.

In 2023, California had the highest Hispanic population in the United States, with over 15.76 million people claiming Hispanic heritage. Texas, Florida, New York, and Illinois rounded out the top five states for Hispanic residents in that year. History of Hispanic people Hispanic people are those whose heritage stems from a former Spanish colony. The Spanish Empire colonized most of Central and Latin America in the 15th century, which began when Christopher Columbus arrived in the Americas in 1492. The Spanish Empire expanded its territory throughout Central America and South America, but the colonization of the United States did not include the Northeastern part of the United States. Despite the number of Hispanic people living in the United States having increased, the median income of Hispanic households has fluctuated slightly since 1990. Hispanic population in the United States Hispanic people are the second-largest ethnic group in the United States, making Spanish the second most common language spoken in the country. In 2021, about one-fifth of Hispanic households in the United States made between 50,000 to 74,999 U.S. dollars. The unemployment rate of Hispanic Americans has fluctuated significantly since 1990, but has been on the decline since 2010, with the exception of 2020 and 2021, due to the impact of the coronavirus (COVID-19) pandemic.

About this dataset

Context

The dataset tabulates the Sycamore population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Sycamore across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Sycamore was 18,682, a 0.16% increase year-by-year from 2022. Previously, in 2022, Sycamore population was 18,652, a decline of 0.14% compared to a population of 18,678 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Sycamore increased by 6,530. In this period, the peak population was 18,682 in the year 2023. The numbers suggest that the population has not reached its peak yet and is showing a trend of further growth. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Sycamore is shown in this column.
• Year on Year Change: This column displays the change in Sycamore population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Sycamore Population by Year. You can refer the same here

About this dataset

Context

The dataset tabulates the Quincy population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Quincy across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Quincy was 38,803, a 0.10% decrease year-by-year from 2022. Previously, in 2022, Quincy population was 38,840, a decline of 0.69% compared to a population of 39,108 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Quincy decreased by 1,899. In this period, the peak population was 40,904 in the year 2011. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Quincy is shown in this column.
• Year on Year Change: This column displays the change in Quincy population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Quincy Population by Year. You can refer the same here

Estimates of effective population size (Ne) for Eastern Massasauga sampled from Carlyle Lake, Illinois.

About this dataset

Context

The dataset tabulates the Sterling population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Sterling across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Sterling was 14,508, a 0.23% decrease year-by-year from 2022. Previously, in 2022, Sterling population was 14,541, a decline of 1.43% compared to a population of 14,752 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Sterling decreased by 1,432. In this period, the peak population was 15,940 in the year 2000. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Sterling is shown in this column.
• Year on Year Change: This column displays the change in Sterling population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Sterling Population by Year. You can refer the same here

About this dataset

Context

The dataset tabulates the Dixon population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Dixon across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Dixon was 15,096, a 0.76% decrease year-by-year from 2022. Previously, in 2022, Dixon population was 15,212, a decline of 0.67% compared to a population of 15,314 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Dixon decreased by 742. In this period, the peak population was 15,838 in the year 2000. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Dixon is shown in this column.
• Year on Year Change: This column displays the change in Dixon population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Dixon Population by Year. You can refer the same here